Looking for a Job? The Three Online Profiles to Build that Can Help Open Doors

(My entire series on how to find a job is here. )

I have spoken with many people who are unemployed looking for a job or want to make a jump from whatever they are doing now to something better. I have already written about how to network with others to find a job, how to strategically prioritize the job application process, and how to nail an interview.

This piece will focus on how to create an online profile that can help you find a job. This two- or three-pronged social media strategy is incredibly helpful in presenting you as an expert professional in whatever field you are working in.

Step 1: Create a LinkedIn profile (and any industry specific online profiles).

Everyone needs a LinkedIn profile, especially when finding a job, so if you don’t have a profile create one. It’s a major hub for job networking in pretty much every industry.

But how to create a LinkedIn profile? For someone who is making a transition to a new field, the best strategy is to position oneself as if one has already done similar work. If you want to continue working in the type of job you’ve always been working in, that’s great; you already demonstrated your experience, but for those who want to make a transition from one field to the other, it can be best to highlight anything you have done that can seem like you have been doing that work or at least something similar.

If you have done something similar in a previous job, even if it’s just one project, blow it up on your LinkedIn description of that job. If you have a job where you can work on a side project that is related to what you want to do, then give it a try. For example, I have advised many who want to become data scientists to incorporate a data science component into whatever they are doing in their current jobs or to create a project at work they do on the side that involves data science. Thus, they can discuss their current work as involving data science work and use that to present themselves as a fledgling data scientist.

People often will describe themselves on LinkedIn as “aspiring data scientist,” “aspiring designer,” etc. Saying you are “aspiring” is the next best alternative if you absolutely cannot describe yourself as already doing it. If you are able to describe yourself as doing it, even if a minor capacity alongside other work, then do it. (And if you don’t have a job at the moment to incorporate a project into, see Step 3.) You will be treated as if your foot is in the door, not as someone knocking and waiting to be let in.

Step 2: Create any industry specific online profiles:

Also, important: if there are specific social medias for the industry you want to work in, create those as well. I’m a data scientist, and for tech, that would be GitHub. In my experience, artists often have an Instagram to showcase your art (frequently a different profile than their personal profile). Video editors often use Fiver. Some industries have specific social media where it all happens. How do you know what profile to create for the industry you want to work in?

Well, if you don’t already know, talk to people in the industry and just ask them (here’s how to network and talk to people in the industry again). They’ll tell you pretty quickly which ones.

Step 3: Work on projects in your new field

This is especially useful for those who are unemployed. Do something in the field. If push comes to shove, work on a personal project in the field, but if you can, do some part-time work helping someone else (networking helps you find these, so see that article; I keep mentioning it because it is important). You can thus list this as work experience. Never mind if it’s only a few hours a week: it’s still work experience. This helps present you as someone already in the field, circumventing the vicious cycle of entry level jobs in a field already requiring having work experience doing it.

For example, ten years ago when I took a data science boot camp during a transition period in between jobs considering becoming a data scientist, I networked extensively to learn about different professions and what people did in the industry. As such, I spoke with someone in charge of a boutique consulting firm who needed a data scientist for a project. I agreed and worked for an hourly wage maybe 4 hours a week on this project. It was actually helpful in itself because it was the first time I did data science in the “real world” outside the simulated environment of my lessons. But I also put it on my LinkedIn as my current experience (the profile didn’t make a distinction between full-time and part-time work experience anyways). My job title on LinkedIn was now officially “data scientist,” and after finishing the bootcamp in several months, I officially had six months experience working as a data scientist. This made me a beginner data scientist in interviews, not an aspiring data scientist, allowing me to circumvent the process of not having had work experience.

The project you work on can be informal. Friends or family may have a project they want you to work on that could fit this. If they officially give you money for your trouble, even if it’s only a few dollars or an ice cream cone, that is even better: on LinkedIn and your resume, it’s now a job. Even a company you started could in theory work. I don’t like the so-called “unpaid internships” because I find them exploitative, but even these could technically work. You don’t have to spend too much time working on them either. Just a few hours a week, and you’re still officially working in the field. People can often fit only a few hours a week into even the busiest schedule.

Step 4: Create a professional website/blog

This can be the most time-consuming but super important step: create a professional website or blog in the subject matter you would like to work in. If it’s data science, make a data science blog that also showcases your data science projects; if your a designer, make a blog about design that also showcases your design work; etc. This will position you as a knowledgeable person contributing ideas in the field.

For example, when I was fresh out of graduate school, looking for a job in data science, I initially created this website (ethno-data.com). My purposes for this blog have evolved overtime, but one of my initial reasons for creating it was to find a job. From that perspective, this website reaped dividends: you’d be surprised at how many people will reach out to me because they have found some of my articles interesting and have a role that might be a good fit for what I do.

Try to pick a specific niche within your field that is interesting to you personally and compelling to at least some others. It doesn’t have to be the most popular idea in the field; more important that it is something you enjoy and feel comfortable nerding out on. You can combine multiple areas of expertise you have, focusing on how they overlap (for me, that was ethnography and data science/AI). Make it reflect you. That both helps sell you and your unique contribution to the field, but it also tends to make it more interesting to you. You won’t want to post on content again and again if it’s not you.

There are so many different platforms to use to build the website (from WordPress to Bluehost to Medium to Squarespace and so on), so do your research on which one works best for you. These platforms tend to walk through the process for non-techies anyways. Set yourself a posting schedule and have at it. Whether you write articles once a week, every other week, every month, matters less. What tends to matter is that you post according to a consistent schedule.

Last but arguably most importantly, mention your articles on LinkedIn and any other social media platform you are using to network. If you post an article in your blog that week, write a statement on LinkedIn (or any other social media you are using) summarizing what you talked about and link to it. This will not only encourage people to read your pieces, but most importantly of all, it will present you online as someone contributing to the field. You are helping to advance your field. As such, people will be more likely to hire you.

Conclusion

That’s it. If you do all four of these, you will have a kick-butt online profile that will help you find a job, even if it’s a profession you are transitioning into. They are all practical things you could set up anytime. With the exception of Step 3, which sometimes requires coordination with others, you can do each of these on your own. You can even get started right now if you want.

Analyzing the 2024 Election: How Democrats Lost the Working Class and What It Means for America’s Future

What happened in the 2024 election, and what can we expect from Donald Trump during these next four years? In our follow-up conversation, Kyle Morrison describes why Kamala Harris and Democrats lost favor among many US Americans and how US voters shifted during the 2024 election. Even though we talked in January, 2025 in the weeks before Trump was sworn into office, his predictions of what to watch out for during a Trump second term still remain salient.

He also describes what Democrats can do to win back power. Voters tend to vote based on how they feel, and he discusses how to resonate with voters in political campaigns in the current age of social media.

Kyle is an anthropologist specializing in US moderate conservative movements, particularly conservatives who do not support Donald Trump or the contemporary Republican party (sometimes also called “Never Trumpers”). He also has years of experience conducting grassroots organizing and developing consensus across competing political perspectives to promote equitable labor practices.

Those Forced Out: Conservatives who Never Supported Donald Trump and the Contemporary Republican Party and its Implications for Presidential Elections – Part 1 of an Interview with Kyle Morrison (Interview #1 in a New Series)

What is it like to feel kicked out of one’s party? What role does social media play in dividing people politically in the United States and Canada, and what can we do to bridge these gaps? And finally, what are the implications of all of these on presidential elections?

I interviewed Kyle Morrison to talk about these questions. He’s an anthropologist who has studied conservatives or those leaning conservative who have felt disgruntled with Donald Trump and the contemporary Republican party (sometimes also called Never Trumpers). Here, he talks about what he learned from talking with them about how they navigate the current divisive political world in the United States and what that may mean for the upcoming 2024 election.

In this first part, we discuss the experiences such conservatives have and the implications for this presidential election and the last several presidential elections.

He also describes how through his research with this group, he learned to listen to and engage with people he does not agree with politically and ways to do that in the current political landscape. He is not a conservative but wanted to use this research to seek to understand those on the “other side.” We in the United States live in one of the most politically divided eras of our history, making such initiatives all the more important to foster empathy and understanding with those one disagrees with.

This is the first interview in a new podcast interview series where I talk with others from around the world to learn how different people navigate life. This first interview focuses on a political anthropology expert in US politics, but my interviews will be of people from different cultures around the world – some experts, some not – to learn more about humanity and the different ways people navigate our complex contemporary world.

Note: We recorded the interview a few days before Joe Biden dropped out of the race and Kamala Harris became the Democratic Party candidate for the election, so you will hear us talk about Biden as the Democratic candidate.

Links for the Materials We Discuss

The Atlantic Monthly Podcast Episode I Mention:

https://www.youtube.com/watch?v=0TJ42eHo6xE&pp=ygUkdGhlIGF0bGFudGljIGhvdyB0byBoYXZlIGFuIGFyZ3VtZW50